Influence Diagrams for Representing Uncertainty in Climate-Related Propositions

In order to respond to policy questions about the potential impacts of climate change it is usually necessary to assemble large quantities of evidence from a variety of sources. Influence diagrams provide a formal mechanism for structuring this evidence and representing its relationship with the climate-related question of interest. When populated with probabilistic measures of belief an influence diagram provides a graphical representation of uncertainty, which can help to synthesize complex and contentious arguments into a relatively simple, yet evidence-based, graphical output.Following unusually damaging floods in October–November 2000 the UK government commissioned research with a view to establishing the extent to which the floods were a manifestation of hydrological climate change. By way of example application, influence diagrams have been used to represent the evidential reasoning and uncertainties in responding to this question. Three alternative approaches to the mathematization of uncertainty in influence diagrams are demonstrated and compared. In situations of information scarcity and imprecise expert judgements, methods based on interval probabilities have proved to be attractive. Interval probabilities can, it is argued, represent ambiguity and ignorance in a more satisfactory manner than the conventional Bayesian alternative. The analysis provides a quantified commentary on the uncertainties in the conclusion that the events of October–November 2000 were extreme, but cannot in themselves be attributed to climate change.     

Radiocarbon Chronology of Ross Sea Drift, Eastern Taylor Valley, Antarctica: Evidence for a Grounded Ice Sheet in the Ross Sea at the Last Glacial Maximum

More than 250 radiocarbon dates of lacustrine algae and marine shells afford a chronology for Ross Sea drift in eastern Taylor Valley. Dates of algae that lived in ice-dammed Glacial Lake Washburn show that grounded Ross Sea ice blocked the mouth of Taylor Valley between 8340 and 23,800 ¹⁴C yr bp . Ross Sea ice was at its maximum position at the Hjorth Hill moraine between 12,700 and 14,600 ¹⁴C yr bp and was within 500m distance of this position as late as 10,794 ¹⁴C yr bp . The implication is that the flow line of the Ross Sea ice sheet which extended around northern Ross Island and across McMurdo Sound to Taylor Valley must have remained intact, and hence that a grounded ice sheet must have existed east of Ross Island as late as 8340 ¹⁴C yr bp . Evidence from ice-dammed lakes in Taylor Valley and from shells from McMurdo Sound suggests grounding-line retreat from the vicinity of Ross Island between 6500 and 8340 ¹⁴C yr bp . If this is correct, then most recession to the present-day grounding line on the Siple Coast took place subsequently in the absence of significant deglacial sea-level rise. Rising sea level may have triggered internal mechanisms within the ice sheet that led to retreat, but did not in itself drive continued ice-sheet recession. Ice retreat, once set in motion, continued in the absence of sea-level forcing. If correct, this hypothesis implies that the grounding line could continue to recede into the interior reservoir of the West Antarctic Ice Sheet.     

'Blood, brain and bones': taking the body seriously in the geography of health and impairment

Summary Recent geography literature has understood 'the body' mainly as representation. This paper argues for an increased recognition of the body as a material entity. Disability is used to illustrate the importance of reinterpreting the biology of the body and mind. This reinterpretation of the body will, the paper concludes, strengthen research into the geography of health and impairment.     

Lateral and subsurface flows impact arctic coastal plain lake water budgets

Arctic thaw lakes are an important source of water for aquatic ecosystems, wildlife, and humans. Many recent studies have observed changes in Arctic surface waters related to climate warming and permafrost thaw; however, explaining the trends and predicting future responses to warming is difficult without a stronger fundamental understanding of Arctic lake water budgets. By measuring and simulating surface and subsurface hydrologic fluxes, this work quantified the water budgets of three lakes with varying levels of seasonal drainage, and tested the hypothesis that lateral and subsurface flows are a major component of the post‐snowmelt water budgets. A water budget focused only on post‐snowmelt surface water fluxes (stream discharge, precipitation, and evaporation) could not close the budget for two of three lakes, even when uncertainty in input parameters was rigorously considered using a Monte Carlo approach. The water budgets indicated large, positive residuals, consistent with up to 70% of mid‐summer inflows entering lakes from lateral fluxes. Lateral inflows and outflows were simulated based on three processes; supra‐permafrost subsurface inflows from basin‐edge polygonal ground, and exchange between seasonally drained lakes and their drained margins through runoff and evapotranspiration. Measurements and simulations indicate that rapid subsurface flow through highly conductive flowpaths in the polygonal ground can explain the majority of the inflow. Drained lakes were hydrologically connected to marshy areas on the lake margins, receiving water from runoff following precipitation and losing up to 38% of lake efflux to drained margin evapotranspiration. Lateral fluxes can be a major part of Arctic thaw lake water budgets and a major control on summertime lake water levels. Incorporating these dynamics into models will improve our ability to predict lake volume changes, solute fluxes, and habitat availability in the changing Arctic. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.     

Is your neighbor your friend? Scan methods for spatial social network hotspot detection

GIS analyses use moving window methods and hotspot detection to identify point patterns within a given area. Such methods can detect clusters of point events such as crime or disease incidences. Yet, these methods do not account for connections between entities, and thus, areas with relatively sparse event concentrations but high network connectivity may go undetected. We develop two scan methods (i.e., moving window or focal processes), EdgeScan and NDScan, for detecting local spatial-social connections. These methods capture edges and network density, respectively, for each node in a given focal area. We apply methods to a social network of Mafia members in New York City in the 1960s and to a 2019 spatial network of home-to-restaurant visits in Atlanta, Georgia. These methods successfully capture focal areas where Mafia members are highly connected and where restaurant visitors are highly local; these results differ from those derived using traditional spatial hotspot analysis using the Getis–Ord Gi* statistic. Finally, we describe how these methods can be adapted to weighted, directed, and bipartite networks and suggest future improvements.     

Impact of land-atmospheric coupling in CFSv2 on drought prediction

Recent summers in the United States have been plagued by intense droughts that have caused significant damage to crops and have had a large impact on society. The ability to forecasts such events would allow for preparations that could help reduce the impact on society. Coupled land–atmosphere–ocean models were created to provide such forecasts but there are large uncertainties associated with their predictions. The predictive skill of these models is particularly low during the convective season due to the weaker connections with the oceans and an increase in the land–atmosphere interactions. To better understand the degradation of forecasts skill during the summer months and its connection to the land–atmosphere interactions we analyze National Centers for Environmental Prediction’s Climate Forecast System Version 2 (CFSv2) in terms of its climatological land–atmosphere interactions. To do this we use a recently developed classification of land–atmosphere interactions and other diagnostic variables to compare the reanalysis from the Climate Forecast System (CFSR) with CFSv2 re-forecasts (CFSRR) over the period 1982–2009. Coupling in the CFSRR tends toward the wet coupling regime for most areas east of the Rocky Mountains. Although the specific mechanism driving CFSRR to wet coupling state varies by region, the overall cause is enhanced vegetation rooting depth, originally implemented to address a near-surface warm bias in CFSR. The long-term tendency to wet coupling precludes the forecast model from consistently predicting and maintaining drought over the continental US.     

A simple carbon cycle representation for economic and policy analyses

Integrated Assessment Models (IAMs) that couple the climate system and the economy require a representation of ocean CO₂ uptake to translate human-produced emissions to atmospheric concentrations and in turn to climate change. The simple linear carbon cycle representations in most IAMs are not however physical at long timescales, since ocean carbonate chemistry makes CO₂ uptake highly nonlinear. No linearized representation can capture the ocean’s dual-mode behavior, with initial rapid uptake and then slow equilibration over ∽10,000 years. In a business-as-usual scenario followed by cessation of emissions, the carbon cycle in the 2007 version of the most widely used IAM, DICE (Dynamic Integrated model of Climate and the Economy), produces errors of ∽2^°C by the year 2300 and ∽6^°C by the year 3500. We suggest here a simple alternative representation that captures the relevant physics and show that it reproduces carbon uptake in several more complex models to within the inter-model spread. The scheme involves little additional complexity over the DICE model, making it a useful tool for economic and policy analyses.